MODELING AND EVALUATION OF A SIMPLE ADAPTIVE ANTENNA ARRAY FOR A WCDMA MOBILE COMMUNICATION

ABSTRACT

This thesis presents the uniform Linear Array model of a simple adaptive antenna array based on signaltointerference plus noise ratio SINR maximization.

The SINR was investigated for a conventional narrow band beam former by varying the number of antenna array elements and number of interfering signals or users. The results were compared with that of omnidirectional antenna. The graph obtained showed significant improvement in SINR as the number of antenna elements increases in the presence of large interferers for odd numbered array.

TABLE OF CONTENTS

Title page i

Certification ii

Approval page iii

Dedication vi

Acknowledgement v

Abstract vii

Table of Contents viii

List of Tables xii

List of Figures xiii

CHAPTER ONE: INTRODUCTION

1.1 Background 1

1.2 Problem statement 2

1.3 Objective of the work 3

1.4 Justification 4

1.5 Scope of the work 5

1.6 Thesis organization 6

CHAPTER TWO: LITERATURE REVIEW

2.1 Review of past related work 8

2.2 Evolution smart antennas 10

2.2.1 Omni directional antennas 10

2.2.2 Directional antennas and sectorized systems 12

2.2.3 Adaptive array antenna development overview of smart antenna technology 14

2.3 Overview of smart antenna technology 18

2.4 Classification of smart antenna 20

2.4.1 Switched beam antennas 21

2.4.2 Dynamically phased array 22

2.4.3 Adaptive array antennas 22

2.5 System elements of a smart antenna 24

2.5.1 Smart antenna receiver 24

2.5.2 Smart antenna transmitter 28

2.6 Antenna array and array geometry 31

2.7 Channel model 33

2.7.1 Mean path loss 34

2.7.2 Fading 37

2.7.3 Slow fading 38

2.7.4 Fast fading 39

2.7.5 Flat fading 41

2.7.6 Doppler spread 41

2.7.7 Delay spread 43

2.7.8 Angle spread 44

2.8 CDMA system model for uplink 45

2.10 Benefits of adaptive antenna array 51

2.12 Adaptive filters 53

CHAPTER THREE: METHODOLOGY AND SYSTEM ANALYSIS

3.1 Introduction 56

3.2 Cell model 57

3.3 Uniform linear array 59

3.4 Fixed weight beamformer 61

3.4.1 Signal modeling 62

3.4.2 Beamformer output 65

3.5 Signal strength and DOA measurement 68

CHAPTER FOUR

4.1 Maximizing signaltointerference and noise ratio

Environment 71

4.2 Summary of results 89

CHAPTER FIVE

5.1 Summary of achievement 90

5.2 problems encountered and solution. 91

5.3 Recommendation and suggestion for further research 92

5.4 Conclusion 92

References 94

Appendix 101

LIST OF TABLES

Table 3.1: Signal strength dBm and DOA 0 measurements 69

Table 4.1: SINR when the number of interferers is two 72

Table 4.2: SINR in the presence of three interferers 74

Table 4.3: SINR in the presence of four interferers 76

Table 4.4: SINR in the presence of six interferers 78

Table 4.5: SINR in the presence of eight interferers 80

Table 4.6: SINR in the presence of ten interferers 81

Table 4.7: SINR in the presence of 12 interferers 82

CHAPTER ONE

INTRODUCTION

1.1 Background

Smart antennas have emerged as one of the leading innovations for achieving highly efficient networks that maximize capacity and improve quality and coverage. Smart antennas provide greater capacity and performance benefits than conventional antennas because they can be used to customize and finetune antenna coverage pattern to the changing traffic or radio frequency RF conditions in a wireless communication system like the WCDMA network.